Railway vehicle intelligent welding all-data collection and analysis system based on structured parameters and use method

Abstract

The invention discloses a rail vehicle intelligent welding all-data collection and analysis system based on structural parameters and a use method, and relates to the technical field of rail transit welding digital production. The system comprises a welding file compiling unit, a welding monitoring execution unit, a welding data processing and analyzing unit, a welding data collecting unit, a welding parameter switching unit and a welding control unit. According to the method, the digital welding process file and the welding parameter package are compiled and issued to the welding machine, the welding monitoring activity is carried out in the mode of binding persons, machines, materials and methods, the welding parameters of the welded welding seam are strictly controlled, the one-time qualification rate of the welding seam is increased to 90%, and the welding quality is improved; welding parameters are monitored in real time, so that a welder carries out welding strictly according to a welding process procedure, and the welding quality problem caused by human factors is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of digital production of rail transit welding, and in particular to a rail vehicle intelligent welding full data collection and analysis system based on structured parameters and a method for using the system. Background Art

[0002] With the advancement and widespread application of information technology, the concept of "digitalization" has become increasingly clear to people. Digital technology generally refers to integrated technologies that use computer hardware and software, interface devices, protocols, and networks as technical means, and are based on information science theories and methods such as the discrete representation, sensing, transmission, processing, storage, execution, and integration of information. Digital welding technology is a key component of the digitalization of manufacturing technology. It involves the following aspects: welding equipment, welding process knowledge, sensing and detection, information processing, process modeling, process controllers, robotic mechanisms, and the implementation of complex system integration through intelligent approaches.

[0003] The goal of digital welding technology is to establish a complete multi-level coordinated welding flexible intelligent manufacturing production line using an integrated flexible welding system. This requires the configuration of an integrated engineering software system to realize the digitization of manufacturing processes and data preparation; integration with the design system to realize the management and control of the manufacturing process and the digitization of manufacturing resource management; the establishment of a manufacturing resource database, a welding parameter database for typical materials and processes, and typical parts; the application of flexible manufacturing engineering technology to improve the overall efficiency of welding equipment applications; the establishment of mathematical models and software models for welding process simulation and emulation systems; the provision of simulation software for welding thermal processes, mechanical processes, molten pool formation processes, and weld metal crystallization processes to facilitate the analysis and prediction of joint microstructure and performance, and to optimize the welding process; and the establishment of an automatic welding quality evaluation system.

[0004] At present, the vast majority of digital welding scenarios are applied to robot welding or automatic welding, and are rarely used for manual welding. Due to the great interference of human factors, manual welding is inferior to robot welding in terms of both the accuracy of process procedures and the quality of welding. However, at present, there are relatively few industrial fields in my country that can apply digital welding on a large scale. Due to the limitations of non-standard welded parts, most industries still use manual welding methods. For manual welding, the use of parameters is often inspected during the welding process, and multiple inspections are carried out after welding to control the welding quality. When welding problems occur, it is often impossible to trace back to the welding parameters, welding materials, base materials, personnel and other information at the time, and the root cause of the welding defects cannot be found.

[0005] Currently, no effective solutions have been proposed for the problems in related technologies. Summary of the Invention

[0006] In response to the problems in the related art, the present invention proposes a rail vehicle intelligent welding full data collection and analysis system based on structured parameters and a method of use to overcome the above-mentioned technical problems existing in the existing related art.

[0007] To this end, the specific technical solutions adopted in the present invention are as follows:

[0008] According to one aspect of the present invention, a rail vehicle intelligent welding full data collection and analysis system based on structured parameters is provided, the system comprising: a welding file compilation unit, a welding monitoring execution unit, a welding data processing and analysis unit, a welding data acquisition unit, a welding parameter switching unit and a welding control unit;

[0009] The welding file preparation unit is used to generate a structured process file based on the first preset coding rule, and transmit the structured process file to the welding monitoring execution unit as a production monitoring benchmark;

[0010] The welding monitoring execution unit is used to achieve real-time monitoring and visualization of the entire welding process, and realize closed-loop traceability of the entire welding process based on the production monitoring benchmark;

[0011] The welding data processing and analysis unit is used to build a welding parameter anomaly detection model using the isolation forest algorithm, perform statistical analysis on the collected welding data, identify abnormal parameters during the welding process, and perform statistics and comparison on the abnormal data based on preset screening conditions;

[0012] Welding data acquisition unit, used to collect data of the entire welding process and transmit welding data between the welding file preparation unit, welding monitoring execution unit, welding data processing and analysis unit, welding parameter switching unit and welding control unit;

[0013] The welding parameter switching unit is used to optimize the welding parameters and generate switching instructions based on the current welding task, production monitoring benchmark and real-time welding status by using parameter matching and dynamic switching algorithms, combined with fuzzy logic control;

[0014] The welding control unit is used to conduct full-process inspections before operations, real-time welding monitoring during operations, and closed-loop inspections of equipment status after operations, thus achieving digital management and control of the entire welding cycle.

[0015] Furthermore, the structured process files in the welding file preparation unit include: file code, file name, product drawing number, project name, work station number, version and change record, specification drawing, welding machine work station drawing and welding process card and parameters.

[0016] Furthermore, the welding monitoring execution unit includes a vehicle archive module, a production planning module, a production management module, a manufacturing management module, a system management module and a visualization module;

[0017] The vehicle archive module is used to manage welding material traceability information and welding process parameter data, achieving component-level production traceability and quality closed-loop during the welding process.

[0018] The production planning module is used to generate the production plan for each station on the same day according to the second preset coding rule, so as to realize the visual control of the workshop operation plan;

[0019] The production management module is used to track all elements of the welding task in real time and realize closed-loop control of task execution status;

[0020] The manufacturing management module is used to achieve full-factor control of welding quality through full-link production process traceability and abnormal dynamic closed-loop management;

[0021] The system management module is used to build a safe operation foundation for the welding monitoring system through role permission configuration and operator basic information maintenance;

[0022] The visualization module is used to form linked monitoring through dual cockpits and build a workshop-level welding full-process data decision-making center.

[0023] Furthermore, the dual cockpits include a work area digital cockpit and a work area welding monitoring cockpit;

[0024] The digital cockpit in the work area is used to locate the production rhythm, quickly identify the location of components, and record and analyze welding power consumption, thereby optimizing workshop energy consumption and reducing production costs.

[0025] The work area welding monitoring cockpit is used to intercept and optimize welding process-level anomalies through real-time alarms on welding machine maps, tracking of process parameter out-of-limits, and dynamic dashboards for consumables.

[0026] Furthermore, the welding data processing and analysis unit includes an abnormal data details module and an abnormal data statistical analysis module;

[0027] Among them, the abnormal data details module is used to build a welding parameter anomaly detection model through the isolation forest algorithm, and perform statistical analysis on the collected welding data to realize the identification of abnormal parameters in the welding process;

[0028] The abnormal data statistical analysis module is used to count and compare abnormal data based on preset screening conditions.

[0029] Furthermore, a welding parameter anomaly detection model is constructed by using the isolation forest algorithm, and statistical analysis is performed on the collected welding data to realize the identification of abnormal parameters in the welding process. The following steps are included:

[0030] Collect welding data and pre-process the welding data using sliding window filtering algorithm and linear interpolation method;

[0031] A welding parameter anomaly detection model is constructed based on the isolation forest algorithm. The preprocessed welding data is input into the welding parameter anomaly detection model to calculate the path length of the preprocessed welding data in the isolation forest.

[0032] Whether the welding data is abnormal is determined based on the path length of the preprocessed welding data in the isolation forest.

[0033] Furthermore, the welding data acquisition unit includes a left data interface, a middle data interface and a right data interface;

[0034] Among them, the data interface on the left is connected to the data interface on the welding power supply, which is used to power the welding parameter acquisition box and distribute and collect welding parameters;

[0035] The intermediate data interface is connected to the welding parameter switching unit and is used to supply power to the welding parameter switching unit and transmit data;

[0036] The data interface on the right is connected to the gas flow sensor and is used to power the gas flow sensor and obtain the shielding gas flow during welding.

[0037] Furthermore, the parameter matching and dynamic switching algorithm is used to optimize the welding parameters according to the current welding task, production monitoring benchmark and real-time welding status, combined with fuzzy logic control, and generate the switching instructions, including the following steps:

[0038] Obtain welding standard parameter set based on current welding task and production monitoring benchmark;

[0039] Dynamically adjust real-time welding parameters based on welding standard parameter sets;

[0040] Use fuzzy logic control to optimize real-time welding parameters and generate switching commands;

[0041] Perform security verification on the switching command to obtain the final switching instruction.

[0042] Furthermore, the welding control unit includes a pre-operation module, an in-operation module, and a post-operation module;

[0043] Among them, the pre-operation module is used to ensure a zero-defect benchmark for welding start-up through digital inspection;

[0044] The in-operation module is used to ensure the stability of the welding process through real-time dynamic monitoring of welding parameters and a fault-fuse task transfer mechanism;

[0045] The post-operation module is used to automatically generate equipment status inspection and production data to achieve a closed-loop welding cycle and traceable archiving.

[0046] According to another aspect of the present invention, a method for using a rail vehicle intelligent welding full data collection and analysis system based on structured parameters is also provided, and the method comprises the following steps:

[0047] S1. The process personnel prepare the structured process file in the welding file preparation unit and welding data processing and analysis unit, complete the file code, file name, product drawing number, project name, and work station number, and upload the specification drawing to the corresponding module;

[0048] S2. Upload the welding design file to the welding file preparation unit, and automatically identify the document sequence, document number and corresponding welding parameters;

[0049] S3. In the welding document preparation unit, click the mouse to select the welding machine, and then click the "Operation" button in the row where the document item in the welding process card and parameter is located in the prescribed order to assign the welding parameter package to the welding machine. After completing the operation of assigning welding parameter packages to all welding machines, click the "Submit" button to proceed with the editing and approval process;

[0050] S4. The workshop manager logs into the welding monitoring execution unit to check the daily plan, monthly plan, and annual plan. After verification, the work area digital cockpit and the work area welding monitoring cockpit are projected onto the workshop on-site display screen;

[0051] S5. The welder turns on the welding machine and waits for the welding data acquisition unit to automatically start self-test. The station manager operates the welding control unit, clicks the "Daily Inspection" button, completes the daily inspection according to the inspection items, and clicks "Submit". Clicks the "Welding Machine Inspection" button, completes the welding machine inspection according to the inspection items, and clicks "Submit". Clicks the "Address Inspection" button, binds the station number and planned project information, and clicks "Submit".

[0052] S6. The dispatcher clicks the "Process File Dispatch" button in the welding control unit to enter the interface, selects the welding process file, selects the workstation, selects the project, and clicks the "Dispatch" button to enter a new interface; selects the welding work drawing of the current project, clicks the "Dispatch" button, and a welder selection dialog box pops up; after selecting the welder, clicks "OK" to complete the dispatch of the current welder, until the dispatch of welders at all workstations is completed;

[0053] S7. Click the "Material QR Code Scan" button in the welding control unit to enter the interface, select the workstation, select the project, select the scan type, and select the component to which it belongs; click the "Scan" button to call the infrared scanning function of the industrial flat panel to scan the material / welding wire. After scanning all materials of the current component, click the "Bind" button to complete the entry and binding of the material information;

[0054] S8. The welder presses the "up" key on the welding parameter switching unit to obtain the work order; then presses the middle "OK" key, the screen displays "Start Welding", and the welding of the first weld begins; after the first weld is completed, press the "right key" to switch to the welding parameters of the second weld, and then press the middle "OK" key to start the welding of the second weld; until all welding work orders are completed, the screen displays "Welding Completed", and the system automatically completes the work report for this beat;

[0055] S9. The workstation manager checks the execution status of each welding machine in real time on the welding control unit or welding monitoring execution unit. If there are any abnormal parameters, the interface will be marked red as an early warning, and the workstation manager will remind the welder to weld within the specified welding parameter range;

[0056] S10: After all welders at this station complete the work order at the current beat, the station manager repeats the operation steps of S6-S9 until all beat tasks for the day are completed;

[0057] S11. The next day, the process personnel log in to the welding document preparation unit and the welding data processing and analysis unit to check the welding data and abnormal welding data of all welding machines yesterday, as well as data comparison information of various dimensions;

[0058] S12. Process personnel shall promptly go to the site to conduct follow-up and documentation based on the content of the exceeded limit, analyze the cause, formulate and verify the measures to resolve such anomalies;

[0059] S13. Process personnel complete the "cause analysis, measures and closed-loop status" of each abnormal item in the welding document preparation unit and the welding data processing and analysis unit, and complete the closed-loop of the entire welding parameter monitoring process.

[0060] The beneficial effects of the present invention are:

[0061] 1. The present invention compiles digital welding process files and welding parameter packages and sends them to the welding machine, binding people, machines, materials, and methods to conduct welding monitoring activities, strictly controlling the welding parameters of the welds, and increasing the one-time pass rate of welds to 90%, thereby improving welding quality. During the production process, information such as shielding gas usage, welding wire usage, and welding energy consumption is collected simultaneously to provide data support for lean production. Through the welding control unit, electronic versions of three-dimensional work instructions, welding process files, and flaw detection process files can be viewed according to the current production rhythm, realizing paperless production site process data. Daily equipment and 5S are inspected online to reduce the use of office paper, save office costs, and meet the requirements of green and low-carbon manufacturing.

[0062] 2. The present invention monitors welding parameters in real time, so that welders can weld strictly in accordance with welding process regulations, avoiding welding quality problems caused by "human factors". Statistical analysis is performed on abnormal welding parameter information to accurately determine the impact of welding process documents, welder skill levels, and welding equipment on welding quality. Based on this statistical analysis, the process department optimizes the process, upgrades equipment, and improves personnel skills. Scan and archive welding wires and materials to facilitate raw material tracing due to product quality issues in the future; collect and save welding process parameters to facilitate electronic data archiving by quality engineers; statistical analysis of welding wire and gas usage allows managers to accurately determine quotas and save production costs. The large-screen billboard visualizes workshop production data, making it easier for process and management personnel to accurately locate production rhythms, quickly identify component production locations, and improve the efficiency of abnormal handling. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0064] Figure 1 This is a principle block diagram of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0065] Figure 2 This is a flow chart of a method for using a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0066] Figure 3 This is a data flow diagram of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0067] Figure 4This is a display diagram of a welding parameter package compilation interface of a welding file compilation unit and a welding data processing and analysis unit of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0068] Figure 5 A welding monitoring system dashboard configuration module and a large-screen display diagram of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0069] Figure 6 This is a physical diagram of a data acquisition device for a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0070] Figure 7 This is a home page interface display diagram of a welding control unit of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0071] Figure 8 This is a diagram showing an interface of a process file distribution module of a welding control unit of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0072] Figure 9 This is one of the interface display diagrams of the material QR code scanning module of the welding control unit of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0073] Figure 10 This is a second diagram showing the interface of a material QR code scanning module of a welding control unit of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0074] Figure 11 This is a third diagram showing the interface of a material QR code scanning module of a welding control unit of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0075] Figure 12 This is a physical diagram of a welding parameter switcher of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0076] Figure 13 This is a display diagram of an in-operation viewing module interface of a welding control unit of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0077] Figure 14This is a diagram showing a work area digital cockpit display interface of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention;

[0078] Figure 15 This is a diagram of a work area welding monitoring cockpit display interface of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to an embodiment of the present invention.

[0079] In the picture:

[0080] 1. Welding document preparation unit; 2. Welding monitoring execution unit; 3. Welding data processing and analysis unit; 4. Welding data acquisition unit; 5. Welding parameter switching unit; 6. Welding control unit. DETAILED DESCRIPTION

[0081] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention. They are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. By referring to these contents, ordinary technicians in this field should be able to understand other possible implementation methods and advantages of the present invention. The components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0082] According to an embodiment of the present invention, a rail vehicle intelligent welding full data collection and analysis system based on structured parameters and a method for using the system are provided.

[0083] The present invention will now be further described with reference to the accompanying drawings and specific embodiments. Figure 1 As shown, according to one embodiment of the present invention, a rail vehicle intelligent welding full data collection and analysis system based on structured parameters is provided, which includes: a welding file preparation unit 1, a welding monitoring execution unit 2, a welding data processing and analysis unit 3, a welding data acquisition unit 4, a welding parameter switching unit 5 and a welding control unit 6.

[0084] The welding document preparation unit 1 is used to generate a structured process file based on a first preset coding rule, and transmit the structured process file to the welding monitoring execution unit 2 as a production monitoring benchmark.

[0085] It should be explained that after the structured process file is compiled, the welding file compilation unit 1 and the welding data processing and analysis unit 3 automatically push the welding work drawing and welding parameter package to the welding monitoring execution unit 2 and store them as a resource package for welding parameter monitoring.

[0086] In this optional embodiment, the structured process file in the welding file preparation unit 1 includes: file code, file name, product drawing number, project name, work station number, version and change record, specification drawing, welding machine work station drawing, welding process card and parameters.

[0087] It should be noted that file codes must be compiled according to the first preset coding rule. For example: PJSPM000-92-210000000-001, where PJS is a fixed field representing the technical department's process file; PM000 is the code for this project, used to match the four-day plan; 92 represents the welding file; 210 represents a component product; and 001 is the serial number of the welding process file for this component.

[0088] The function of the workstation number is to call up the welding machine workstation map and send the welding process file to the corresponding workstation in the workshop.

[0089] The welding station map shows the actual location of the welding machines in each station. The map includes the general shape of the station, the station number, and the welding machine. The welding machine icon on the map includes the welding machine number. You can click on it with the mouse and there are single recall and delete buttons, which are used to attach the corresponding welding parameters to the welding machine.

[0090] Welding process cards and parameters can be imported into CAD software using a specific formatted field to identify the corresponding WPS number and welding parameters. For example, if two WPS numbers, "1-PZW-A01-01-001" and "2-PZW-A01-01-002," are compiled and numbered in a CAD file, the corresponding WPS number and welding parameters will be displayed in the welding process card and parameter fields after importing the CAD file.

[0091] The welding monitoring execution unit 2 is used to realize real-time monitoring and visualization of the entire welding process, and realize closed-loop traceability of the entire welding process based on the production monitoring benchmark.

[0092] In this optional embodiment, the welding monitoring execution unit 2 includes a vehicle archive module, a production planning module, a production management module, a manufacturing management module, a system management module and a visualization module;

[0093] Among them, the vehicle archive module is used to manage welding material traceability information and welding process parameter data, realizing component-level production traceability and quality closed loop during the welding process.

[0094] It should be noted that the vehicle file module contains material information and welding wire information for each item and component. The material information includes the material name, material code, material serial number / batch number + furnace number, and supplier name.

[0095] The vehicle file module also includes all welding data information tables for each project, each workstation, and each welding machine. The welding data information table includes 20 items, including project name, column number, vehicle number, process file number, process file name, WPS number, workstation, welding machine, welder number, welder name, work step number, WPS number, real-time voltage, rated voltage, real-time current, rated current, gas flow, wire feed speed, overlimit type, and occurrence time.

[0096] The production planning module is used to generate the production plan for each station on the day according to the second preset coding rule, so as to realize the visual management and control of the workshop operation plan.

[0097] It's important to note that the production plan module contains the daily production plan for each machine. The production plan content is coded according to the second preset coding rule. For example: PM000-XXX Project-Chassis-2801, where PM000 represents the project code; XXX Project represents the Chinese name of the project; Chassis represents the name of the welded component; and 2801 represents the vehicle number. Production plans can be automatically obtained through integration with other systems or manually imported from an Excel file.

[0098] The production management module is used to track all elements of the day's welding tasks in real time, achieving closed-loop control of task execution status.

[0099] It should be noted that the production management module displays data related to welding production assignments for the day. This includes file number, file name, project information, vehicle model information, work area and workstation information, welder information, welding machine information, process file version information, and task completion status.

[0100] The manufacturing management module is used to achieve full-factor control of welding quality through full-link production process traceability and abnormal dynamic closed-loop management.

[0101] It should be explained that the manufacturing management module includes three sub-modules: material traceability, production traceability, and exception management. The material traceability sub-module queries material information according to project, vehicle number, and component. The production traceability sub-module queries welding production parameter data according to project, vehicle number, workstation, and welder. The welding production parameter information includes file name, file number, vehicle number, step number, WPS number, actual / rated voltage, actual / rated current, gas flow, wire feed speed, vehicle type, workstation, welder, welding machine, time, and file version information. The exception management sub-module queries welding production exception data according to project, workstation, date, file name, and welder. The content includes project name, file number, file name, workstation, step number, WPS number, WPS number, welder information, welding machine information, actual current / rated current, actual voltage / rated voltage, gas flow, wire feed speed, and time information.

[0102] The system management module is used to build a safe operation foundation for the welding monitoring system through role permission configuration and operator basic information maintenance.

[0103] It's important to note that the System Management module consists of two submodules: Role Management and User Management. The Role Management submodule includes the role name, permission characters, role order, status, and menu permissions. The User Management submodule adds or imports a single system operator, and its content includes user ID, user name, user nickname, department, mobile phone number, status, and creation time.

[0104] The visualization module is used to form linked monitoring through dual cockpits and build a workshop-level welding full-process data decision-making center.

[0105] It's important to clarify that the large-screen dashboard (i.e., the visualization module) displays information about the day's production tasks, workshop personnel and equipment configurations, process flow, welding process monitoring, welding parameter collection and display, and NCR information. The large-screen dashboard includes a work area digital cockpit and a work area welding monitoring cockpit.

[0106] In this optional embodiment, the dual cockpits include a work area digital cockpit and a work area welding monitoring cockpit;

[0107] The digital cockpit in the work area is used to locate the production rhythm, quickly identify the location of components, and record and analyze welding power consumption, thereby optimizing workshop energy consumption and reducing production costs.

[0108] The work area welding monitoring cockpit is used to intercept and optimize welding process-level anomalies through real-time alarms on welding machine maps, tracking of process parameter out-of-limits, and dynamic dashboards for consumables.

[0109] It's important to note that the work area's digital cockpit includes information on production plan fulfillment rates, process flow, NCR issuance, welding machine energy consumption, and personnel and equipment configuration. The cockpit displays the work area's daily production rhythm and task completion status, as well as information on NCR issuance and closures by the quality department. The cockpit also displays the real-time power consumption of welding machines within the work area and the total power consumption from the previous day. This allows process and management personnel to accurately track production rhythms and quickly identify component locations. It also records and analyzes welding power usage, optimizing energy consumption and reducing production costs.

[0110] The work area welding monitoring cockpit displays the monthly welding star, monthly workstation welding rankings, key welding consumables statistics, welding machine maps, welding machine status, welding duration, and real-time welding parameter and parameter out-of-limit alarm information. The work area welding monitoring cockpit displays the current day's and yesterday's welding wire and shielding gas usage, as well as real-time monitoring of welding process parameters. The welding machine map displays real-time welding parameter out-of-limit alarms. Alarms include workstation, personnel, project information, and a comparison of standard welding parameters with out-of-limit parameters. The welding machine is also highlighted in red to alert personnel.

[0111] The welding data processing and analysis unit 3 is used to construct a welding parameter anomaly detection model through the isolation forest algorithm, perform statistical analysis on the collected welding data, realize the identification of abnormal parameters in the welding process, and perform statistics and comparison on the abnormal data based on preset screening conditions.

[0112] In this optional embodiment, the welding data processing and analysis unit 3 includes an abnormal data details module and an abnormal data statistical analysis module;

[0113] Among them, the abnormal data details module is used to build a welding parameter anomaly detection model through the isolation forest algorithm, and perform statistical analysis on the collected welding data to realize the identification of abnormal parameters in the welding process.

[0114] It should be noted that the abnormal data details module displays a pie chart of the total welding data percentage for all workstations upon entering the interface. The total welding data includes normal welding data, current limit data, voltage limit data, and all limit data. Below the pie chart, the abnormal data details are displayed. The items include serial number, welding machine number, rated current, actual current, rated voltage, actual voltage, weld limit rate, limit type, project, train, vehicle, workstation, platform, welder, gas flow rate, abnormality occurrence time, work step number, WPS number, on-site actual parameter limit tracking, cause analysis, measures, and closed-loop status.

[0115] Items exceeding limits (actual current, actual voltage, and weld exceedance rate) are highlighted in red. The exceedance rate is calculated as: the exceedance time for a weld / welding time. Welds with less than 20% of the limit are automatically deleted and not considered exceedances. After the exceedance points are generated and displayed, process personnel must edit and save the text for the actual parameter exceedance tracking / cause analysis / measures.

[0116] The closed-loop status is as follows: After an out-of-limit item is generated, it will automatically be filled in with "Not Closed" in red. Clicking this box will pop up a dialog box. Select Closed and fill in the closure details. Click OK, and the "Closed" text will turn black. After selecting Closed, you must fill in the closure details; otherwise, clicking OK will not work. The abnormal data details items can be filtered by project, workstation, station, time period, welding machine number, WPS number, welder name, process file name, and vehicle number to display the required abnormal data.

[0117] The abnormal data statistical analysis module is used to count and compare abnormal data based on preset screening conditions.

[0118] It should be explained that in the abnormal data statistics analysis module, if you click the abnormal data statistics button without adding filtering conditions, the following contents will be displayed: 1. Display all over-limit data by project; 2. Display all over-limit data by workstation; 3. Display over-limit data by subdividing workstations according to the proportion of different over-limit types; 4. Display the workstation rankings of last month; 5. Display the welder rankings of last month; 6. When adding time filtering, display the data of the corresponding time period.

[0119] When a project is selected: 1. Display the over-limit data of all workstations in the project; 2. When filtering by time and vehicle number, display the over-limit data of the corresponding time period.

[0120] Abnormal data is counted based on preset filtering conditions. When a certain project is selected, a certain workstation is also filtered: 1. The over-limit data of this project and this workstation are displayed (by default, the three dimensions of WPS / welder / welder are displayed. When WPS / welder / welder are selected, the corresponding over-limit data is displayed); 2. When filtering by time and vehicle number, the over-limit data of the corresponding time period is displayed.

[0121] Compare abnormal data based on preset screening conditions. The first screening condition comparison function:

[0122] 1. Click the +Compare button to add a new filter bar. 2. After selecting different items in the two filter bars, all over-limit data of the two items will be compared. 3. After adding vehicle number and work station filter conditions, the over-limit data of the corresponding vehicle number and work station will be displayed. 4. There is no limit to the number of +Compares.

[0123] Compare abnormal data based on preset filtering conditions, the second filtering condition comparison function:

[0124] 1. After selecting the same item and different vehicle numbers in the two filter bars, all over-limit data of the two vehicles will be compared; 2. After adding the workstation filter condition, the over-limit data of the corresponding workstation will be displayed.

[0125] Compare abnormal data based on preset filtering conditions, the third filtering condition comparison function:

[0126] 1. Select the same project, different vehicle numbers, and the same workstation in the two filter bars, then select WPS. This will display the comparative over-limit data for the same WPS on the two vehicles. 2. Select the same project, different vehicle numbers, and the same workstation in the two filter bars, then select Welder. This will display the comparative over-limit data for the same welder on the two vehicles. 3. Select the same project, different vehicle numbers, and the same workstation in the two filter bars, then select Welder. This will display the comparative over-limit data for the same welder on the two vehicles. 4. Select the same project, different vehicle numbers, and the same workstation in the two filter bars, then select Work Step Number. This will display the comparative over-limit data for the same Work Step Number on the two vehicles.

[0127] In this optional embodiment, a welding parameter anomaly detection model is constructed using an isolation forest algorithm, and statistical analysis is performed on the collected welding data to identify abnormal parameters during the welding process, including the following steps:

[0128] Collect welding data and pre-process the welding data using sliding window filtering algorithm and linear interpolation method;

[0129] A welding parameter anomaly detection model is constructed based on the isolation forest algorithm. The preprocessed welding data is input into the welding parameter anomaly detection model to calculate the path length of the preprocessed welding data in the isolation forest.

[0130] Whether the welding data is abnormal is determined based on the path length of the preprocessed welding data in the isolation forest.

[0131] It is important to note that welding data processing and analysis unit 3 preprocesses the raw data collected during the welding process, including missing values ​​and other interfering information. A sliding window filtering algorithm is used to smooth time series data such as welding current and voltage. A fixed-size sliding window is used to traverse the data, and a weighted average of the data within the window is performed to remove invalid data interference. Missing data is also filled in using linear interpolation of adjacent data to ensure data integrity and accuracy.

[0132] Welding data processing and analysis unit 3 constructs a welding parameter anomaly detection model based on the isolation forest algorithm. Parameters such as welding current, voltage, and welding speed are used as feature vectors. Multiple isolation trees are constructed to calculate the path length of each data point. Data points with shorter path lengths are more likely to be identified as an outlier. When processing large-scale data, a divide-and-conquer approach is employed to partition the original dataset into multiple sub-datasets. Isolation tree models are then constructed in parallel. Finally, the results from each sub-model are integrated to rapidly identify abnormal parameter fluctuations during the welding process, such as sudden current changes or abnormal voltage drops, providing timely warnings of potential welding quality issues.

[0133] The welding data acquisition unit 4 is used to collect data of the entire welding process and transmit welding data between the welding file preparation unit 1, the welding monitoring execution unit 2, the welding data processing and analysis unit 3, the welding parameter switching unit 5 and the welding control unit 6.

[0134] It should be noted that the welding data acquisition device 4 (i.e., the welding data acquisition device unit) is mounted on the welding power supply housing. Its dimensions are 120mm × 30mm × 160mm, and the housing is made of ABS engineering plastic. The welding data acquisition device 4 transmits data via Wi-Fi signals. After the work is dispatched, the device receives the welding parameters for the current production cycle and uses them to control the welder to automatically switch to the preset welding parameters. The welder cannot adjust the welding current and welding voltage at will, and can only adjust them within ±8% of the parameter values ​​specified in the WPS. Simultaneously, welding parameters are collected twice per second during the welding process. The collected data is stored locally and pushed to the welding monitoring system. The device supports breakpoint resuming.

[0135] In this optional embodiment, the welding data acquisition unit 4 includes a left data interface, a middle data interface and a right data interface;

[0136] Among them, the data interface on the left is connected to the data interface on the welding power supply, which is used to power the welding parameter acquisition box and distribute and collect welding parameters;

[0137] The intermediate data interface is connected to the welding parameter switching unit 5 and is used to supply power to the welding parameter switching unit 5 and transmit data;

[0138] The data interface on the right is connected to the gas flow sensor and is used to power the gas flow sensor and obtain the shielding gas flow during welding.

[0139] It's important to note that the lower end of the welding data acquisition device has three data transmission interfaces. The left data interface is connected to the data interface on the welding power supply, and its function is to power the welding parameter acquisition box and distribute and collect welding parameters. The middle data interface is connected to the welding parameter switch 5 (i.e., the welding parameter switching unit) for powering the welding parameter switch 5 and transmitting data. The right data interface is connected to the gas flow sensor for powering the gas flow sensor and obtaining the shielding gas flow during welding. The screen of the welding data acquisition device displays the task number, preset current / voltage, actual current / voltage, gas flow, and accumulated gas flow.

[0140] The welding parameter switching unit 5 is used to utilize parameter matching and dynamic switching algorithms to optimize welding parameters according to the current welding task, production monitoring benchmark and real-time welding status, and to generate switching instructions in combination with fuzzy logic control.

[0141] It should be explained that the welding parameter switch 5 (i.e., the welding parameter switching unit) is fixed next to the wire feeder panel, and is connected to the welding data acquisition device 4 via a wired method, and the outer sheath of the data cable is made of fire-resistant and high-temperature resistant rubber material.

[0142] The welding parameter switch 5 is made of ABS engineering plastic and measures 40mm × 20mm × 80mm. It features a 1-inch LED display on the top front, which displays the current welding task's WPS number, step number, and the standard and upper and lower limits for welding current and voltage. Positioning buttons are arranged in a circular pattern at the bottom front of the switch, with up, down, left, and right buttons on the outer circle and an OK button in the center. These buttons are used to start tasks, switch parameters, and end tasks.

[0143] In this optional embodiment, the parameter matching and dynamic switching algorithm is used to optimize the welding parameters according to the current welding task, production monitoring benchmark and real-time welding status, combined with fuzzy logic control, and generate the switching instruction, including the following steps:

[0144] Obtain welding standard parameter set based on current welding task and production monitoring benchmark;

[0145] Dynamically adjust real-time welding parameters based on welding standard parameter sets;

[0146] Use fuzzy logic control to optimize real-time welding parameters and generate switching commands;

[0147] Perform security verification on the switching command to obtain the final switching instruction.

[0148] It should be noted that the welding parameter switcher 5 uses a parameter matching and dynamic switching algorithm to obtain a standard parameter set based on the current task, adjust parameters based on the real-time welding status, and apply fuzzy logic control to optimize parameters, generate switching instructions, and verify safety. The specific pseudo code of the built-in core algorithm of the welding parameter switcher is as follows:

[0149]

[0150]

[0151]

[0152] The welding control unit 6 is used to perform full-process inspection before operation, real-time welding monitoring during operation, and closed-loop inspection of equipment status after operation, realizing digital management and control of the entire welding cycle.

[0153] It should be explained that the welding control unit 6 uses an industrial tablet, the operating system is developed based on Android, and uses TYPE-C interface and USB3.0 interface for communication; the protection level is IP67; the shock resistance is 1-1.5 meters; the memory capacity is 4GB; the hard disk type is SATA; the storage space is 64GB; and the screen size is 9.7 inches.

[0154] In this optional embodiment, the welding control unit includes a pre-operation module, an in-operation module, and a post-operation module;

[0155] Among them, the pre-operation module is used to ensure zero-defect benchmark for welding start-up through digital inspection.

[0156] It should be explained that the pre-operation module includes daily inspection, welding machine status inspection, process file viewing, address inspection, process file distribution, and material QR code scanning functions. Daily inspection and welding machine status inspection are for daily 5S inspection and welding machine status inspection at the workstation before starting work, forming electronic records and sending them to the welding monitoring system for storage. Address inspection and process file viewing allow welding operators to view the electronic version of the relevant process files for the day's production projects on the industrial tablet. Address inspection is to bind project information to the workstation, which is used to display the process flow on the large-screen billboard. Process file distribution is to distribute the work order after the inspection is completed. After selecting the workstation, welding machine, welder, and project information in turn, the work order is distributed. The system automatically retrieves the welding parameter package of the corresponding project and component and sends it to the welding data acquisition device, and controls the welding parameters of each step according to the parameter content of the welding parameter package. The material QR code scanning is to scan the QR code of the current beat profiles, parts, and welding wire before formal welding, record their information, and save it to the welding monitoring system to form traceability of production materials.

[0157] The in-operation module is used to ensure the stability of the welding process through real-time dynamic monitoring of welding parameters and fault-fuse task transfer mechanism.

[0158] It's important to note that the "On-Job" module consists of two submodules: "On-Job Display" and "Welder Fault Submission." In the "On-Job Display" module, you can view the current project, completion progress, welding parameters, and any parameter violations for the welder at that station in real time. If a welder experiences a sudden malfunction or data transmission issue during operation, you can reassign the task to another welder, forcibly terminate the task, and report it to maintenance for repair.

[0159] The post-operation module is used to automatically generate equipment status inspection and production data to achieve a closed-loop welding cycle and traceable archiving.

[0160] It's important to note that the post-job module includes both a welding status check and a daily check. Click the Welder Status Check button to verify that the welder is functioning properly and shutting down. Then, click Submit to complete the post-job equipment check. After completing the 5S at the workstation, click Daily Check to confirm the post-job check. Submitting the check completes all tasks for the day, automatically generating a spreadsheet of the relevant data and saving it to the welding monitoring system.

[0161] According to another embodiment of the present invention, a method for using a rail vehicle intelligent welding full data collection and analysis system based on structured parameters is also provided. The method comprises the following steps:

[0162] S1. The process personnel prepare the structured process file in the welding file preparation unit 1 and the welding data processing and analysis unit 3, complete the file code, file name, product drawing number, project name, and work station number, and upload the specification drawing to the corresponding module;

[0163] S2. Upload the welding design file to the welding file preparation unit 1, and automatically identify the document sequence, document number and corresponding welding parameters;

[0164] S3. In the welding document preparation unit 1, click the mouse to select the welding machine, and then click the "Operation" button in the row where the document item in the welding process card and parameter is located in the prescribed order to assign the welding parameter package to the welding machine. After completing the operation of assigning the welding parameter package to all welding machines, click the "Submit" button to proceed with the editing and approval process;

[0165] S4. The workshop manager logs into the welding monitoring execution unit 2 to check the daily plan, monthly plan, and annual plan. After verification, the work area digital cockpit and the work area welding monitoring cockpit are projected onto the workshop on-site display screen.

[0166] S5. The welder turns on the welding machine and waits for the welding data acquisition unit 4 to automatically start self-test. The workstation manager operates the welding control unit 6, clicks the "Daily Inspection" button, completes the daily inspection according to the inspection items, and clicks "Submit". The welder manager clicks the "Welding Machine Inspection" button, completes the welding machine inspection according to the inspection items, and clicks "Submit". The welder manager clicks the "Address Inspection" button, binds the workstation number and planned project information, and clicks "Submit".

[0167] S6. The dispatcher clicks the "Process File Dispatch" button in the welding control unit 6 and enters the interface, selects the welding process file, selects the work station, selects the project, clicks the "Dispatch" button and enters a new interface; selects the welding work drawing of the current project, clicks the "Dispatch" button, and a welder selection dialog box pops up; after selecting the welder, clicks "OK" to complete the dispatch of the current welder, until the dispatch of the welders at the work station is completed;

[0168] S7. Click the "Material QR Code Scan" button in the welding control unit 6 to enter the interface, select the workstation, select the project, select the scan type, and select the component to which it belongs; click the "Scan" button to call the infrared scanning function of the industrial tablet to scan the material / welding wire. After scanning all materials of the current component, click the "Bind" button to complete the entry and binding of the material information;

[0169] S8. The welder presses the "up" key of the welding parameter switching unit 5 to obtain the work order; then presses the middle "OK" key, the screen displays "Start Welding", and the welding of the first weld is started; after the first weld is completed, press the "right key" to switch to the welding parameters of the second weld, and then press the middle "OK" key to start the welding of the second weld; until all welding work orders are completed, the screen displays "Welding Completed", and the system automatically completes the work report for this beat;

[0170] S9. The station manager checks the welding execution status of each welding machine on the welding control unit 6 or the welding monitoring execution unit 2 in real time. If there is any abnormal parameter, the interface will be marked red as an early warning, and the station manager will remind the welder to weld within the specified welding parameter range;

[0171] S10: After all welders at this station complete the work order at the current beat, the station manager repeats the operation steps of S6-S9 until all beat tasks for the day are completed;

[0172] S11. The next day, the process personnel log in to the welding document preparation unit 1 and the welding data processing and analysis unit 3 to check the welding data and abnormal welding data of all welding machines yesterday and data comparison information of various dimensions;

[0173] S12. Process personnel shall promptly go to the site to conduct follow-up and documentation based on the content of the exceeded limit, analyze the cause, formulate and verify the measures to resolve such anomalies;

[0174] S13. Process personnel complete the "cause analysis, measures and closed-loop status" of each abnormal item in the welding document preparation unit and the welding data processing and analysis unit, and complete the closed-loop of the entire welding parameter monitoring process.

[0175] It needs to be explained that, Figure 2 As shown in FIG, it is a flow chart of the use of the rail vehicle intelligent welding full data collection and analysis system based on structured parameters. Figure 3 Figure 2 shows the data flow diagram for the structured parameter-based rail vehicle intelligent welding full-data collection and analysis system. Process personnel compile structured process files in welding file compilation unit 1 and welding data processing and analysis unit 3, completing the file code, file name, product drawing number, project name, and vehicle type / workstation number, and then upload the specification drawing to the corresponding module.

[0176] like Figure 4 The figure shows the welding parameter package compilation interface display diagram of the welding file compilation unit 1 and the welding data processing and analysis unit 3. Compiled in the CAD file:

[0177] 1-PZW-A01-03-008;

[0178] 2-PZW-A01-03-011;

[0179] 3-PZW-A01-01-061;

[0180] 4-PZW-A01-03-080.

[0181] There are 4 WPS numbers in total and they are numbered in sequence as "1-, 2-, 3-, 4-". After the CAD file is imported, the WPS number and welding parameters (weld bead, welding current, welding voltage) of the corresponding sequence are displayed in the welding process card and parameter column.

[0182] Step 1: In the welding machine station diagram, click the mouse to display the red dotted box to select the welding machine. Then, in the prescribed order (1, 2, 3, 4), click the "Operation" button in the row containing the WPS item in the welding process card and parameters to assign the welding parameter package to the welding machine. There are corresponding "Withdraw" and "Delete" icons below the welding machine diagram. When editing, you can withdraw individual welding parameter information or delete all welding parameter information. Repeat the above steps until all welding machines have been assigned welding parameter packages. Click the "Submit" button to proceed with the editing and approval process, and automatically send the file to the welding monitoring execution unit 2.

[0183] Step 2: If Figure 5 The figure shows the dashboard configuration module and large-screen display for welding monitoring execution unit 2. Workshop managers log in to welding monitoring execution unit 2 and access the dashboard configuration module to review daily, monthly, and annual plans. Once verified, the work area digital cockpit and welding monitoring cockpit are projected onto the workshop's large screen for on-site display.

[0184] Step 3: If Figure 6 As shown in FIG, it is a physical picture of the welding data acquisition device 4. Figure 7 The figure shows the homepage interface of the welding control unit 6. The welder turns on the welding machine and waits for the welding data acquisition device 4 to automatically start up and self-test. When the device MAC address appears at the bottom of the display, it indicates that the device is booting normally. The station manager uses the industrial tablet to log in to the welding control unit 6, clicks the "Daily Inspection" button, completes the daily inspection according to the inspection items, and clicks "Submit". They also click the "Welding Machine Inspection" button, completes the welding machine inspection according to the inspection items, and clicks "Submit". They click the "Address Inspection" button, bind the station number and planned project information, and click "Submit".

[0185] Step 4: If Figure 8-10 Figure 6 shows the interface for the process file dispatch module in the welding control unit 6. Click the "Process File Dispatch" button to enter the interface. Select the welding process file, select the workstation, and select the project. Click the "Dispatch" button to enter a new interface. Select the welding work drawing (welding parameter package) for the current project and click the "Dispatch" button. The welder selection dialog box will pop up. After selecting a welder, click "OK" to complete the dispatch for the current welder. Repeat the above steps to dispatch welders to the workstation.

[0186] Step 5: If Figure 11 Figure 6 shows the interface of the material QR code scanning module in the welding control unit 6. Click the "Material QR Code Scan" button to enter the interface, select the workstation, select the project, select the scan type (material / welding wire), and select the corresponding component. Click the "Scan" button to use the industrial tablet's infrared scanning function to scan the material / welding wire. After scanning all materials for the current component, click the "Bind" button to complete the material information entry and binding.

[0187] Step 6: If Figure 12 The figure shows a physical image of the welding parameter switch 5. The welder presses the "up" button on the welding parameter switch 5 to obtain the work order. Then, they press the middle "OK" button. The screen displays "Start welding" to begin welding the first weld. After the first weld is completed, they press the "right button" to switch to the welding parameters for the second weld and press the middle "OK" button to start welding the second weld. They repeat these steps until the work order is completed. The screen displays "weld finish" and the system automatically completes the work report for this cycle.

[0188] Step 7: If Figure 13 As shown in FIG, it is a diagram showing the module interface of the welding control unit 6 during operation. Figure 14 As shown in the figure, it is the interface diagram of the large screen display of the digital cockpit in the work area. Figure 15 The following is a diagram of the large-screen display interface of the welding monitoring cockpit in the work area. Workstation managers can view the performance of each welding machine in real time on an industrial tablet or large display screen. If any parameter exceeds the limit, the interface will be marked red as an alarm, and the station manager will remind the welder to weld within the specified welding parameter range.

[0189] Step 8: After all welders at this station complete the work order in the current beat, the station manager repeats the operation steps from step 4 to step 7 until all beat tasks for the day are completed.

[0190] Step 9: The process personnel log in to the welding document preparation unit 1 and the welding data processing and analysis unit 3 to view the welding data and abnormal (out-of-limit) welding data of all welding machines yesterday and data comparison information of various dimensions.

[0191] Step 10: Process personnel will promptly go to the site to track and document the contents of the violations, analyze the causes, formulate and verify measures to resolve such anomalies.

[0192] Step 11: The process personnel complete the "cause analysis, measures, and closed-loop status" of each abnormal item in the welding document preparation unit 1 and the welding data processing and analysis unit 3, completing the closed loop of the entire welding parameter monitoring process.

[0193] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A rail vehicle intelligent welding full data collection and analysis system based on structured parameters, characterized in that: The system includes: a welding document preparation unit, a welding monitoring execution unit, a welding data processing and analysis unit, a welding data acquisition unit, a welding parameter switching unit and a welding control unit; The welding file preparation unit is configured to generate a structured process file based on a first preset coding rule, and transmit the structured process file to the welding monitoring execution unit as a production monitoring benchmark; The welding monitoring execution unit is used to achieve real-time monitoring and visualization of the entire welding process, and to achieve closed-loop traceability of the entire welding process based on the production monitoring benchmark; The welding data processing and analysis unit is used to construct a welding parameter anomaly detection model using the isolation forest algorithm, perform statistical analysis on the collected welding data, identify abnormal parameters in the welding process, and perform statistics and comparison on the abnormal data based on preset screening conditions; The welding data acquisition unit is used to collect data of the entire welding process and transmit welding data between the welding file preparation unit, the welding monitoring execution unit, the welding data processing and analysis unit, the welding parameter switching unit and the welding control unit; The welding parameter switching unit is used to optimize the welding parameters and generate switching instructions based on the current welding task, production monitoring benchmark and real-time welding status by using parameter matching and dynamic switching algorithms and combining fuzzy logic control; The welding control unit is used to perform full-process inspection before operation, real-time welding monitoring during operation, and closed-loop inspection of equipment status after operation, thereby realizing digital management and control of the entire welding cycle.

2. A rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to claim 1, characterized in that: The structured process files in the welding file compilation unit include: file code, file name, product drawing number, project name, work station number, version and change record, specification drawing, welding machine work station drawing, welding process card and parameters.

3. The rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to claim 1 is characterized in that: The welding monitoring execution unit includes a vehicle file module, a production planning module, a production management module, a manufacturing management module, a system management module and a visualization module; The vehicle archive module is used to manage welding material traceability information and welding process parameter data, achieving component-level production traceability and quality closed loop during the welding process; The production planning module is used to generate a production plan for each station on the same day according to the second preset coding rule, so as to realize visual management and control of the workshop operation plan; The production management module is used to track all elements of the welding task assigned on the day in real time, and realize closed-loop control of the task execution status; The manufacturing management module is used to achieve full-factor control of welding quality through full-link production process traceability and abnormal dynamic closed-loop management; The system management module is used to build a safe operation base for the welding monitoring system through role authority configuration and operator basic information maintenance; The visualization module is used to form linked monitoring through dual cockpits and build a workshop-level welding full-process data decision-making center.

4. The rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to claim 3 is characterized in that: The dual cockpits include a work area digital cockpit and a work area welding monitoring cockpit; The digital cockpit in the work area is used to locate the production rhythm, quickly identify the location of components, and record and analyze welding power consumption, thereby optimizing workshop energy consumption and reducing production costs. The work area welding monitoring cockpit is used to build welding process-level abnormality interception and optimization through real-time alarms on welding machine maps, tracking of process parameter out-of-limits, and dynamic dashboards for consumables.

5. The rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to claim 1 is characterized in that: The welding data processing and analysis unit includes an abnormal data details module and an abnormal data statistical analysis module; The abnormal data details module is used to construct a welding parameter anomaly detection model using the isolation forest algorithm, and perform statistical analysis on the collected welding data to identify abnormal parameters during the welding process. The abnormal data statistical analysis module is used to collect statistics and compare abnormal data based on preset screening conditions.

6. The rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to claim 5 is characterized in that: The method of constructing a welding parameter anomaly detection model by using the isolation forest algorithm and performing statistical analysis on the collected welding data to identify abnormal parameters during the welding process includes the following steps: Collect welding data and pre-process the welding data using sliding window filtering algorithm and linear interpolation method; A welding parameter anomaly detection model is constructed based on the isolation forest algorithm. The preprocessed welding data is input into the welding parameter anomaly detection model to calculate the path length of the preprocessed welding data in the isolation forest. Whether the welding data is abnormal is determined based on the path length of the preprocessed welding data in the isolation forest.

7. The rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to claim 1 is characterized in that: The welding data acquisition unit includes a left data interface, a middle data interface and a right data interface; The left data interface is connected to the data interface on the welding power supply, and is used to supply power to the welding parameter acquisition box and to distribute and collect welding parameters; The intermediate data interface is connected to the welding parameter switching unit and is used to supply power to the welding parameter switching unit and transmit data; The right data interface is connected to the gas flow sensor and is used to supply power to the gas flow sensor and obtain the shielding gas flow during welding.

8. The rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to claim 1 is characterized in that: The method of utilizing parameter matching and dynamic switching algorithm to optimize welding parameters according to the current welding task, production monitoring benchmark and real-time welding status in combination with fuzzy logic control to generate switching instructions includes the following steps: Obtain welding standard parameter set based on current welding task and production monitoring benchmark; Dynamically adjust real-time welding parameters based on welding standard parameter sets; Use fuzzy logic control to optimize real-time welding parameters and generate switching commands; Perform security verification on the switching command to obtain the final switching instruction.

9. The rail vehicle intelligent welding full data collection and analysis system based on structured parameters according to claim 1 is characterized in that: The welding control unit includes a pre-operation module, an in-operation module and a post-operation module; The pre-operation module is used to ensure a zero-defect benchmark for welding start-up through digital inspection; The in-operation module is used to ensure the stability of the welding process through real-time dynamic monitoring of welding parameters and a fault-fuse task transfer mechanism; The post-operation module is used to realize the closed loop of welding cycle and traceable archiving through equipment status inspection and automatic generation of production data.

10. A method for using a rail vehicle intelligent welding full data collection and analysis system based on structured parameters, for implementing the use of a rail vehicle intelligent welding full data collection and analysis system based on structured parameters as claimed in any one of claims 1 to 9, characterized in that: The method of use includes the following steps: S1. The process personnel prepare the structured process file in the welding file preparation unit and welding data processing and analysis unit, complete the file code, file name, product drawing number, project name, and work station number, and upload the specification drawing to the corresponding module; S2. Upload the welding design file to the welding file preparation unit, and automatically identify the document sequence, document number and corresponding welding parameters; S3. In the welding document preparation unit, click the mouse to select the welding machine, and then click the operation buttons in the rows where the document items in the welding process card and parameters are located in the prescribed order to assign welding parameter packages to the welding machines. After all welding parameters are assigned to all welding machines, click the Submit button to proceed with the editing and approval process. S4. The workshop manager logs into the welding monitoring execution unit to check the daily plan, monthly plan, and annual plan. After verification, the work area digital cockpit and the work area welding monitoring cockpit are projected onto the workshop on-site display screen; S5. The welder turns on the welding machine and waits for the welding data acquisition unit to automatically start self-test. The workstation manager operates the welding control unit, clicks the daily inspection button, completes the daily inspection according to the inspection items, and clicks Submit. The welder manager clicks the welding machine inspection button, completes the welding machine inspection according to the inspection items, and clicks Submit. The welder manager clicks the address inspection button, binds the workstation number and planned project information, and clicks Submit. S6. The dispatcher clicks the process file dispatch button in the welding control unit and enters the interface. Select the welding process file, select the workstation, select the project, click the dispatch button and enter the new interface. Select the welding work drawing of the current project, click the dispatch button, and the welder selection dialog box pops up. After selecting the welder, click OK to complete the dispatch of the current welder until the dispatch of welders at all workstations is completed. S7. Click the material QR code scanning button in the welding control unit to enter the interface, select the workstation, select the project, select the scanning type, and select the component to which it belongs; click the scan button to call the infrared scanning function of the industrial tablet to scan the material / welding wire. After scanning all materials of the current component, click the bind button to complete the entry and binding of the material information; S8. The welder presses the up key on the welding parameter switching unit to obtain the work order; then presses the middle confirm key, and the screen displays "Start Welding" to start welding the first weld; after the first weld is completed, press the right key to switch to the welding parameters for the second weld, and then press the middle confirm key to start welding the second weld; until all welding work orders are completed, the screen displays "Welding Completed" and the system automatically completes the work report for this beat; S9. The workstation manager checks the execution status of each welding machine in real time on the welding control unit or welding monitoring execution unit. If there are any abnormal parameters, the interface will be marked red as an early warning, and the workstation manager will remind the welder to weld within the specified welding parameter range; S10: After all welders at this station complete the work order at the current beat, the station manager repeats the operation steps of S6-S9 until all beat tasks for the day are completed; S11. The next day, the process personnel log in to the welding document preparation unit and the welding data processing and analysis unit to check the welding data and abnormal welding data of all welding machines yesterday, as well as data comparison information of various dimensions; S12. Process personnel shall promptly go to the site to conduct follow-up and documentation based on the content of the exceeded limit, analyze the cause, formulate and verify the measures to resolve such anomalies; S13. Process personnel complete the cause analysis, measures and closed-loop status of each abnormal item in the welding document preparation unit and welding data processing and analysis unit, and complete the closed loop of the entire welding parameter monitoring process.

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